{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# How to Use Forecasters in Merlion\n",
    "\n",
    "This notebook will guide you through using all the key features of forecasters in Merlion. Specifically, we will explain\n",
    "\n",
    "1. Initializing a forecasting model (including ensembles and automatic model selectors)\n",
    "1. Training the model\n",
    "1. Producing a forecast with the model\n",
    "1. Visualizing the model's predictions\n",
    "1. Quantitatively evaluating the model\n",
    "1. Saving and loading a trained model\n",
    "1. Simulating the live deployment of a model using a `ForecastEvaluator`\n",
    "\n",
    "We will be using a single example time series for this whole notebook. We load it now:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Has missing data: False\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "700 points in train split, 48 points in test split.\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "from merlion.utils.time_series import TimeSeries\n",
    "from ts_datasets.forecast import M4\n",
    "\n",
    "# Load the time series\n",
    "# time_series is a time-indexed pandas.DataFrame\n",
    "# trainval is a time-indexed pandas.Series indicating whether each timestamp is for training or testing\n",
    "time_series, metadata = M4(subset=\"Hourly\")[5]\n",
    "trainval = metadata[\"trainval\"]\n",
    "\n",
    "# Is there any missing data?\n",
    "timedeltas = np.diff(time_series.index)\n",
    "print(f\"Has missing data: {any(timedeltas != timedeltas[0])}\")\n",
    "\n",
    "# Visualize the time series and draw a dotted line to indicate the train/test split\n",
    "fig = plt.figure(figsize=(10, 6))\n",
    "ax = fig.add_subplot(111)\n",
    "ax.plot(time_series)\n",
    "ax.axvline(time_series[trainval].index[-1], ls=\"--\", lw=\"2\", c=\"k\")\n",
    "plt.show()\n",
    "\n",
    "# Split the time series into train/test splits, and convert it to Merlion format\n",
    "train_data = TimeSeries.from_pd(time_series[trainval])\n",
    "test_data  = TimeSeries.from_pd(time_series[~trainval])\n",
    "print(f\"{len(train_data)} points in train split, \"\n",
    "      f\"{len(test_data)} points in test split.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Initialization\n",
    "\n",
    "In this notebook, we will use three different forecasting models:\n",
    "1. ARIMA (a classic stochastic process model)\n",
    "2. Prophet (Facebook's popular time series forecasting model)\n",
    "3. MSES (the Multi-Scale Exponential Smoothing model, developed in-house)\n",
    "\n",
    "Let's start by initializing each of them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import models & configs\n",
    "from merlion.models.forecast.arima import Arima, ArimaConfig\n",
    "from merlion.models.forecast.prophet import Prophet, ProphetConfig\n",
    "from merlion.models.forecast.smoother import MSES, MSESConfig\n",
    "\n",
    "# Import data pre-processing transforms\n",
    "from merlion.transform.base import Identity\n",
    "from merlion.transform.resample import TemporalResample\n",
    "\n",
    "# All models are initialized using the syntax ModelClass(config),\n",
    "# where config is a model-specific configuration object. This is where\n",
    "# you specify any algorithm-specific hyperparameters, as well as any\n",
    "# data pre-processing transforms.\n",
    "\n",
    "# ARIMA assumes that input data is sampled at a regular interval,\n",
    "# so we set its transform to resample at that interval. We must also specify\n",
    "# a maximum prediction horizon.\n",
    "config1 = ArimaConfig(max_forecast_steps=100, order=(20, 1, 5),\n",
    "                      transform=TemporalResample(granularity=\"1h\"))\n",
    "model1  = Arima(config1)\n",
    "\n",
    "\n",
    "# Prophet has no real assumptions on the input data (and doesn't require\n",
    "# a maximum prediction horizon), so we skip data pre-processing by using\n",
    "# the Identity transform.\n",
    "config2 = ProphetConfig(max_forecast_steps=None, transform=Identity())\n",
    "model2  = Prophet(config2)\n",
    "\n",
    "\n",
    "# MSES assumes that the input data is sampled at a regular interval,\n",
    "# and requires us to specify a maximum prediction horizon. We will\n",
    "# also specify its look-back hyperparameter to be 60 here\n",
    "config3 = MSESConfig(max_forecast_steps=100, max_backstep=60,\n",
    "                     transform=TemporalResample(granularity=\"1h\"))\n",
    "model3  = MSES(config3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we have initialized the individual models, we will also combine them in two different ensembles: `ensemble` simply takes the mean prediction of each individual model, and `selector` selects the best individual model based on its sMAPE (symmetric Mean Average Precision Error). The sMAPE is a metric used to evaluate the quality of a continuous forecast. For ground truth $y \\in \\mathbb{R}^T$ and prediction $\\hat{y} \\in \\mathbb{R}^T$, the sMAPE is computed as\n",
    "\n",
    "$$\n",
    "\\mathrm{sMAPE}(y, \\hat{y}) = \\frac{200}{T} \\sum_{t = 1}^{T} \\frac{\\lvert \\hat{y}_t - y_t \\rvert}{\\lvert\\hat{y}_t\\rvert + \\lvert y_t \\rvert}\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from merlion.evaluate.forecast import ForecastMetric\n",
    "from merlion.models.ensemble.combine import Mean, ModelSelector\n",
    "from merlion.models.ensemble.forecast import ForecasterEnsemble, ForecasterEnsembleConfig\n",
    "\n",
    "# The ForecasterEnsemble is a forecaster, and we treat it as a first-class model.\n",
    "# Its config takes a combiner object, specifying how you want to combine the \n",
    "# predictions of individual models in the ensemble. There are two ways to specify\n",
    "# the actual models in the ensemble, which we cover below.\n",
    "\n",
    "# The first way to specify the models in the ensemble is to provide them when\n",
    "# initializing the ForecasterEnsembleConfig.\n",
    "#\n",
    "# The combiner here will simply take the mean prediction of the ensembles here\n",
    "ensemble_config = ForecasterEnsembleConfig(\n",
    "    combiner=Mean(), models=[model1, model2, model3])\n",
    "ensemble = ForecasterEnsemble(config=ensemble_config)\n",
    "\n",
    "\n",
    "# Alternatively, you can directly specify the models when initializing the\n",
    "# ForecasterEnsemble itself.\n",
    "#\n",
    "# The combiner here uses the sMAPE to compare individual models, and\n",
    "# selects the model with the lowest sMAPE\n",
    "selector_config = ForecasterEnsembleConfig(\n",
    "    combiner=ModelSelector(metric=ForecastMetric.sMAPE))\n",
    "selector = ForecasterEnsemble(\n",
    "    config=selector_config, models=[model1, model2, model3])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Training\n",
    "\n",
    "All forecasting models (and ensembles) share the same API for training. The `train()` method returns the model's predictions and standard error of those predictions on the training data. Note that the standard error is just `None` if the model doesn't support uncertainty estimation (this is the case for MSES and ensembles)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Arima...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "17:42:09 - cmdstanpy - INFO - Chain [1] start processing\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Training Prophet...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "17:42:09 - cmdstanpy - INFO - Chain [1] done processing\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Training MSES...\n",
      "\n",
      "Training ensemble...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "17:42:20 - cmdstanpy - INFO - Chain [1] start processing\n",
      "17:42:20 - cmdstanpy - INFO - Chain [1] done processing\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Training model selector...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ForecastEvaluator: 100%|██████████| 500400/500400 [00:00<00:00, 3420724.07it/s]\n",
      "17:42:31 - cmdstanpy - INFO - Chain [1] start processing\n",
      "17:42:32 - cmdstanpy - INFO - Chain [1] done processing\n",
      "ForecastEvaluator: 100%|██████████| 500400/500400 [00:00<00:00, 1342155.82it/s]\n",
      "ForecastEvaluator: 100%|██████████| 500400/500400 [00:01<00:00, 407983.30it/s] \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Done!\n"
     ]
    }
   ],
   "source": [
    "print(f\"Training {type(model1).__name__}...\")\n",
    "forecast1, stderr1 = model1.train(train_data)\n",
    "\n",
    "print(f\"\\nTraining {type(model2).__name__}...\")\n",
    "forecast2, stderr2 = model2.train(train_data)\n",
    "\n",
    "print(f\"\\nTraining {type(model3).__name__}...\")\n",
    "forecast3, stderr3 = model3.train(train_data)\n",
    "\n",
    "print(\"\\nTraining ensemble...\")\n",
    "forecast_e, stderr_e = ensemble.train(train_data)\n",
    "\n",
    "print(\"\\nTraining model selector...\")\n",
    "forecast_s, stderr_s = selector.train(train_data)\n",
    "\n",
    "print(\"Done!\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Inference\n",
    "\n",
    "To obtain a forecast from a trained model, we simply call `model.forecast()` with the Unix timestamps at which we the model to generate a forecast. In many cases, you may obtain these directly from a time series as shown below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Truncate the test data to ensure that we are within each model's maximum\n",
    "# forecast horizon.\n",
    "sub_test_data = test_data[:50]\n",
    "\n",
    "# Obtain the time stamps corresponding to the test data\n",
    "time_stamps = sub_test_data.univariates[sub_test_data.names[0]].time_stamps\n",
    "\n",
    "# Get the forecast & standard error of each model. These are both\n",
    "# merlion.utils.TimeSeries objects. Note that the standard error is None for\n",
    "# models which don't support uncertainty estimation (like MSES and all\n",
    "# ensembles).\n",
    "forecast1, stderr1 = model1.forecast(time_stamps=time_stamps)\n",
    "forecast2, stderr2 = model2.forecast(time_stamps=time_stamps)\n",
    "\n",
    "# You may optionally specify a time series prefix as context. If one isn't\n",
    "# specified, the prefix is assumed to be the training data. Here, we just make\n",
    "# this dependence explicit. More generally, this feature is useful if you want\n",
    "# to use a pre-trained model to make predictions on data further in the future\n",
    "# from the last time it was trained.\n",
    "forecast3, stderr3 = model3.forecast(time_stamps=time_stamps, time_series_prev=train_data)\n",
    "\n",
    "# The same options are available for ensembles as well, though the stderr is None\n",
    "forecast_e, stderr_e = ensemble.forecast(time_stamps=time_stamps)\n",
    "forecast_s, stderr_s = selector.forecast(time_stamps=time_stamps, time_series_prev=train_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Visualization and Quantitative Evaluation\n",
    "\n",
    "It is fairly transparent to visualize a model's forecast and also quantitatively evaluate the forecast, using standard metrics like sMAPE. We show examples for all five models below.\n",
    "\n",
    "Below, we quantitatively evaluate the models using the sMAPE metric. However, the `ForecastMetric` enum includes a number of other options as well. In general, you may use the syntax\n",
    "```\n",
    "ForecastMetric.<metric_name>.value(ground_truth=ground_truth, predict=forecast)\n",
    "```\n",
    "where `<metric_name>` is the name of the evaluation metric (see the API docs for details and more options), `ground_truth` is the original time series, and `forecast` is the forecast returned by the model. We show concrete examples with `ForecastMetric.sMAPE` below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Arima sMAPE is 3.472\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from merlion.evaluate.forecast import ForecastMetric\n",
    "\n",
    "# We begin by computing the sMAPE of ARIMA's forecast (scale is 0 to 100)\n",
    "smape1 = ForecastMetric.sMAPE.value(ground_truth=sub_test_data,\n",
    "                                    predict=forecast1)\n",
    "print(f\"{type(model1).__name__} sMAPE is {smape1:.3f}\")\n",
    "\n",
    "# Next, we can visualize the actual forecast, and understand why it\n",
    "# attains this particular sMAPE. Since ARIMA supports uncertainty\n",
    "# estimation, we plot its error bars too.\n",
    "fig, ax = model1.plot_forecast(time_series=sub_test_data,\n",
    "                               plot_forecast_uncertainty=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Prophet sMAPE is 2.947\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# We begin by computing the sMAPE of Prophet's forecast (scale is 0 to 100)\n",
    "smape2 = ForecastMetric.sMAPE.value(sub_test_data, forecast2)\n",
    "print(f\"{type(model2).__name__} sMAPE is {smape2:.3f}\")\n",
    "\n",
    "# Next, we can visualize the actual forecast, and understand why it\n",
    "# attains this particular sMAPE. Since Prophet supports uncertainty\n",
    "# estimation, we plot its error bars too.\n",
    "# Note that we can specify time_series_prev here as well, though it\n",
    "# will not be visualized unless we also supply the keyword argument\n",
    "# plot_time_series_prev=True.\n",
    "fig, ax = model2.plot_forecast(time_series=sub_test_data,\n",
    "                               time_series_prev=train_data,\n",
    "                               plot_forecast_uncertainty=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MSES sMAPE is 4.377\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# We begin by computing the sMAPE of MSES's forecast (scale is 0 to 100)\n",
    "smape3 = ForecastMetric.sMAPE.value(sub_test_data, forecast3)\n",
    "print(f\"{type(model3).__name__} sMAPE is {smape3:.3f}\")\n",
    "\n",
    "# Next, we visualize the actual forecast, and understand why it \n",
    "# attains this particular sMAPE.\n",
    "fig, ax = model3.plot_forecast(time_series=sub_test_data,\n",
    "                               plot_forecast_uncertainty=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ensemble sMAPE is 2.505\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compute the sMAPE of the ensemble's forecast (scale is 0 to 100)\n",
    "smape_e = ForecastMetric.sMAPE.value(sub_test_data, forecast_e)\n",
    "print(f\"Ensemble sMAPE is {smape_e:.3f}\")\n",
    "\n",
    "# Visualize the forecast.\n",
    "fig, ax = ensemble.plot_forecast(time_series=sub_test_data,\n",
    "                                 plot_forecast_uncertainty=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Selector sMAPE is 3.472\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compute the sMAPE of the selector's forecast (scale is 0 to 100)\n",
    "smape_s = ForecastMetric.sMAPE.value(sub_test_data, forecast_s)\n",
    "print(f\"Selector sMAPE is {smape_s:.3f}\")\n",
    "\n",
    "# Visualize the forecast.\n",
    "fig, ax = selector.plot_forecast(time_series=sub_test_data,\n",
    "                                 plot_forecast_uncertainty=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Saving & Loading Models\n",
    "\n",
    "All models have a `save()` method and `load()` class method. Models may also be loaded with the assistance of the `ModelFactory`, which works for arbitrary models. The `save()` method creates a new directory at the specified path, where it saves a `json` file representing the model's config, as well as a binary file for the model's state.\n",
    "\n",
    "We will demonstrate these behaviors using our `Prophet` model (`model2`) for concreteness."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Prophet Config\n",
      "{'daily_seasonality': 'auto',\n",
      " 'dim': 1,\n",
      " 'exog_aggregation_policy': 'Mean',\n",
      " 'exog_missing_value_policy': 'ZFill',\n",
      " 'exog_transform': {'bias': None,\n",
      "                    'name': 'MeanVarNormalize',\n",
      "                    'normalize_bias': True,\n",
      "                    'normalize_scale': True,\n",
      "                    'scale': None},\n",
      " 'holidays': None,\n",
      " 'invert_transform': True,\n",
      " 'max_forecast_steps': None,\n",
      " 'seasonality_mode': 'additive',\n",
      " 'target_seq_index': 0,\n",
      " 'transform': {'name': 'Identity'},\n",
      " 'uncertainty_samples': 100,\n",
      " 'weekly_seasonality': 'auto',\n",
      " 'yearly_seasonality': 'auto'}\n"
     ]
    }
   ],
   "source": [
    "import json\n",
    "import os\n",
    "import pprint\n",
    "from merlion.models.factory import ModelFactory\n",
    "\n",
    "# Save the model\n",
    "os.makedirs(\"models\", exist_ok=True)\n",
    "path = os.path.join(\"models\", \"prophet\")\n",
    "model2.save(path)\n",
    "\n",
    "# Print the config saved\n",
    "pp = pprint.PrettyPrinter()\n",
    "with open(os.path.join(path, \"config.json\")) as f:\n",
    "    print(f\"{type(model2).__name__} Config\")\n",
    "    pp.pprint(json.load(f))\n",
    "\n",
    "# Load the model using Prophet.load()\n",
    "model2_loaded = Prophet.load(dirname=path)\n",
    "\n",
    "# Load the model using the ModelFactory\n",
    "model2_factory_loaded = ModelFactory.load(name=\"Prophet\", model_path=path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can do the same exact thing with ensembles! Note that the ensemble stores its underlying models in a nested structure. Additionally, the combiner (which is saved in the `ForecasterEnsembleConfig`), keeps track of the sMAPE achieved by each model (the `metric_values` key). This is all reflected in the config."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Selector Config\n",
      "{'combiner': {'_override_models_used': {},\n",
      "              'abs_score': False,\n",
      "              'metric': 'ForecastMetric.sMAPE',\n",
      "              'metric_values': [5.3927462062042695,\n",
      "                                6.993034179559698,\n",
      "                                14.33041679538694],\n",
      "              'n_models': 3,\n",
      "              'name': 'ModelSelector'},\n",
      " 'dim': 1,\n",
      " 'exog_aggregation_policy': 'Mean',\n",
      " 'exog_missing_value_policy': 'ZFill',\n",
      " 'exog_transform': {'bias': None,\n",
      "                    'name': 'MeanVarNormalize',\n",
      "                    'normalize_bias': True,\n",
      "                    'normalize_scale': True,\n",
      "                    'scale': None},\n",
      " 'invert_transform': True,\n",
      " 'max_forecast_steps': None,\n",
      " 'models': [{'dim': 1,\n",
      "             'exog_aggregation_policy': 'Mean',\n",
      "             'exog_missing_value_policy': 'ZFill',\n",
      "             'exog_transform': {'bias': None,\n",
      "                                'name': 'MeanVarNormalize',\n",
      "                                'normalize_bias': True,\n",
      "                                'normalize_scale': True,\n",
      "                                'scale': None},\n",
      "             'invert_transform': True,\n",
      "             'max_forecast_steps': 100,\n",
      "             'name': 'Arima',\n",
      "             'order': [20, 1, 5],\n",
      "             'target_seq_index': 0,\n",
      "             'transform': {'aggregation_policy': 'Mean',\n",
      "                           'granularity': 3600.0,\n",
      "                           'missing_value_policy': 'Interpolate',\n",
      "                           'name': 'TemporalResample',\n",
      "                           'origin': 0.0,\n",
      "                           'remove_non_overlapping': True,\n",
      "                           'trainable_granularity': False}},\n",
      "            {'daily_seasonality': 'auto',\n",
      "             'dim': 1,\n",
      "             'exog_aggregation_policy': 'Mean',\n",
      "             'exog_missing_value_policy': 'ZFill',\n",
      "             'exog_transform': {'bias': None,\n",
      "                                'name': 'MeanVarNormalize',\n",
      "                                'normalize_bias': True,\n",
      "                                'normalize_scale': True,\n",
      "                                'scale': None},\n",
      "             'holidays': None,\n",
      "             'invert_transform': True,\n",
      "             'max_forecast_steps': None,\n",
      "             'name': 'Prophet',\n",
      "             'seasonality_mode': 'additive',\n",
      "             'target_seq_index': 0,\n",
      "             'transform': {'name': 'Identity'},\n",
      "             'uncertainty_samples': 100,\n",
      "             'weekly_seasonality': 'auto',\n",
      "             'yearly_seasonality': 'auto'},\n",
      "            {'accel_weight': 1.0,\n",
      "             'dim': 1,\n",
      "             'eta': 0.0,\n",
      "             'inflation': 1.0,\n",
      "             'invert_transform': True,\n",
      "             'max_backstep': 60,\n",
      "             'max_forecast_steps': 100,\n",
      "             'name': 'MSES',\n",
      "             'optimize_acc': True,\n",
      "             'phi': 2.0,\n",
      "             'recency_weight': 0.5,\n",
      "             'rho': 0.0,\n",
      "             'target_seq_index': 0,\n",
      "             'transform': {'aggregation_policy': 'Mean',\n",
      "                           'granularity': 3600.0,\n",
      "                           'missing_value_policy': 'Interpolate',\n",
      "                           'name': 'TemporalResample',\n",
      "                           'origin': 0.0,\n",
      "                           'remove_non_overlapping': True,\n",
      "                           'trainable_granularity': False}}],\n",
      " 'target_seq_index': 0,\n",
      " 'transform': {'name': 'Identity'},\n",
      " 'verbose': False}\n"
     ]
    }
   ],
   "source": [
    "# Save the selector\n",
    "path = os.path.join(\"models\", \"selector\")\n",
    "selector.save(path)\n",
    "\n",
    "# Print the config saved. Note that we've saved all individual models,\n",
    "# and their paths are specified under the model_paths key.\n",
    "pp = pprint.PrettyPrinter()\n",
    "with open(os.path.join(path, \"config.json\")) as f:\n",
    "    print(f\"Selector Config\")\n",
    "    pp.pprint(json.load(f))\n",
    "\n",
    "# Load the selector\n",
    "selector_loaded = ForecasterEnsemble.load(dirname=path)\n",
    "\n",
    "# Load the selector using the ModelFactory\n",
    "selector_factory_loaded = ModelFactory.load(name=\"ForecasterEnsemble\", model_path=path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulating Live Model Deployment\n",
    "\n",
    "A typical model deployment scenario is as follows:\n",
    "1. Train an initial model on some recent historical data\n",
    "1. At a regular interval `cadence`, obtain the model's forecast for a certain `horizon`\n",
    "1. At a regular interval `retrain_freq`, retrain the entire model on the most recent data\n",
    "1. Optionally, specify a maximum amount of data (`train_window`) that the model should use for training\n",
    "\n",
    "We provide a `ForecastEvaluator` object which simulates the above deployment scenario, and also allows a user to evaluate the quality of the forecaster according to an evaluation metric of their choice. We illustrate two examples below, using ARIMA for the first example, and the model selector for the second."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "from merlion.evaluate.forecast import ForecastEvaluator, ForecastEvaluatorConfig, ForecastMetric\n",
    "\n",
    "def create_evaluator(model):\n",
    "    # Re-initialize the model, so we can re-train it from scratch\n",
    "    model.reset()\n",
    "\n",
    "    # Create an evaluation pipeline for the model, where we\n",
    "    # -- get the model's forecast every hour\n",
    "    # -- have the model forecast for a horizon of 6 hours\n",
    "    # -- re-train the model every 12 hours\n",
    "    # -- when we re-train the model, retrain it on only the past 2 weeks of data\n",
    "    evaluator = ForecastEvaluator(\n",
    "        model=model, config=ForecastEvaluatorConfig(\n",
    "            cadence=\"1h\", horizon=\"6h\", retrain_freq=\"12h\", train_window=\"14d\")\n",
    "    )\n",
    "    return evaluator"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, let's evaluate ARIMA."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ForecastEvaluator: 100%|██████████| 169200/169200 [00:12<00:00, 13919.39it/s]\n"
     ]
    }
   ],
   "source": [
    "# Obtain the results of running the evaluation pipeline for ARIMA.\n",
    "# These result objects are to be treated as a black box, and should be\n",
    "# passed directly to the evaluator's evaluate() method.\n",
    "model1_evaluator = create_evaluator(model1)\n",
    "model1_train_result, model1_test_result = model1_evaluator.get_predict(\n",
    "    train_vals=train_data, test_vals=test_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Arima sMAPE: 2.014\n",
      "Arima RMSE:  142.828\n"
     ]
    }
   ],
   "source": [
    "# Evaluate ARIMA's sMAPE and RMSE\n",
    "smape = model1_evaluator.evaluate(\n",
    "    ground_truth=test_data,\n",
    "    predict=model1_test_result,\n",
    "    metric=ForecastMetric.sMAPE)\n",
    "rmse  = model1_evaluator.evaluate(\n",
    "    ground_truth=test_data,\n",
    "    predict=model1_test_result,\n",
    "    metric=ForecastMetric.RMSE)\n",
    "print(f\"{type(model1).__name__} sMAPE: {smape:.3f}\")\n",
    "print(f\"{type(model1).__name__} RMSE:  {rmse:.3f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we will evaluate the ensemble (taking the mean prediction of ARIMA, Prophet, and MSES every time the models are called)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "17:43:09 - cmdstanpy - INFO - Chain [1] start processing\n",
      "17:43:09 - cmdstanpy - INFO - Chain [1] done processing\n",
      "ForecastEvaluator:  26%|██▌       | 43200/169200 [00:09<00:29, 4298.97it/s]17:43:28 - cmdstanpy - INFO - Chain [1] start processing\n",
      "17:43:28 - cmdstanpy - INFO - Chain [1] done processing\n",
      "ForecastEvaluator:  51%|█████     | 86400/169200 [00:25<00:20, 3994.83it/s]17:43:43 - cmdstanpy - INFO - Chain [1] start processing\n",
      "17:43:43 - cmdstanpy - INFO - Chain [1] done processing\n",
      "ForecastEvaluator:  77%|███████▋  | 129600/169200 [00:40<00:09, 4108.92it/s]17:43:59 - cmdstanpy - INFO - Chain [1] start processing\n",
      "17:43:59 - cmdstanpy - INFO - Chain [1] done processing\n",
      "ForecastEvaluator: 100%|██████████| 169200/169200 [00:56<00:00, 2979.61it/s]\n"
     ]
    }
   ],
   "source": [
    "# Obtain the results of running the evaluation pipeline for the ensemble.\n",
    "# These result objects are to be treated as a black box, and should be\n",
    "# passed directly to the evaluator's evaluate() method.\n",
    "ensemble_evaluator = create_evaluator(ensemble)\n",
    "ensemble_train_result, ensemble_test_result = ensemble_evaluator.get_predict(\n",
    "    train_vals=train_data, test_vals=test_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ensemble sMAPE: 2.914\n",
      "Ensemble RMSE:  211.616\n"
     ]
    }
   ],
   "source": [
    "# Evaluate the selector's sMAPE and RMSE\n",
    "smape = ensemble_evaluator.evaluate(\n",
    "    ground_truth=test_data,\n",
    "    predict=ensemble_test_result,\n",
    "    metric=ForecastMetric.sMAPE)\n",
    "rmse  = ensemble_evaluator.evaluate(\n",
    "    ground_truth=test_data,\n",
    "    predict=ensemble_test_result,\n",
    "    metric=ForecastMetric.RMSE)\n",
    "print(f\"Ensemble sMAPE: {smape:.3f}\")\n",
    "print(f\"Ensemble RMSE:  {rmse:.3f}\")"
   ]
  }
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